Insights Accelerator
Accelerating market research output for consulting teams with a self-service analytics platform
The Problem
How can we democratize access to complex market analyses, enabling non-technical users to generate rapid consumer insights independently?
The Insights Accelerator began as a suite of Python scripts aimed at conducting common market analyses. While technically robust, the tool posed significant usability challenges:
• Confusing terminology that created a barrier to understanding
• Knowledge of Python was required, resulting in low adoption among non-technical users
Process
1. Interviewed both technical and non-technical users to understand their interactions with the existing tool and identify areas for improvement.
• Non-technical users found the Python scripts intimidating and hard to navigate
• The timeline of conducting an analysis end-to-end could take up to 3 days
• Both types of users indicated a need for clearer terminology and a more intuitive interface to increase adoption
2. Outlined an information architecture that organized the top analyses into a tabbed interface with a linear flow, making it easier for users to navigate and stay on task.
Using insights from research interviews, we landed on a simple tabbed architecture with one key linear flow, running an analysis. This streamlined and focused structure enables users to navigate the tool effortlessly and remain on task.
3. Created wireframes for key screens and features to gather early feedback and explore different layout options.
4. Applied Deloitte's style guide for visual consistency.
5. Refined screens to develop high-fidelity mockups.
6. Conducted usability testing with users and iterated designs based on feedback.
• "I'm not sure where the data comes from" ➝ Added expandable sections explaining how data is sourced and how results are calculated.
• "Some of the terminology is confusing. What are the benefits of each analysis?" ➝ Renamed the tool "Insights Accelerator" and rewrote internal labels to reflect business value, not developer jargon.
Results
100%
Adoption among non-technical users post-launch.
3X
Reduction in time spent on conducting an analysis.
Enhanced Collaboration
Between technical and non-technical teams through a shared vocabulary.
Lessons learned
• Clear communication bridges technical divides: Simplifying terminology and aligning the tool's design with user expectations significantly improved accessibility.
• User involvement is key to successful design: Regular feedback loops with end-users ensured the final product met their needs and preferences.
